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Investigating tomographic reconstruction with a priori geometrical information

机译:利用先验几何信息研究层析成像重建

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摘要

A novel strategy to perform tomographic image reconstruction is presented, based on the integration of a priori information about the target image. Such information may come from a different imaging tool or a synthetic model. For a given image quality, providing a priori image information reduces the amount of image information to be reconstructed. According to the data processing inequality this requires less input data or physical measurements, therefore reducing exposure to ionising radiation. A prototype algorithm is described, consisting of a penalized ART where some a priori edge information is encoded in an inhomogeneous, anisotropic smoothing kernel. The algorithm is tested on a 2-dimensional set-up based on the Shepp-Logan phantom.
机译:基于有关目标图像的先验信息的集成,提出了一种执行断层图像重建的新颖策略。此类信息可能来自其他成像工具或合成模型。对于给定的图像质量,提供先验图像信息会减少要重建的图像信息量。根据数据处理不平等,这需要较少的输入数据或物理测量,因此减少了对电离辐射的暴露。描述了一种原型算法,该算法由惩罚性ART组成,其中一些先验边缘信息在不均匀的各向异性平滑内核中编码。该算法在基于Shepp-Logan体模的二维设置上进行了测试。

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